User Purchase Intention Prediction Based on Improved Deep Forest

Widely used deep neural networks currently face limitations in achieving optimal performance for purchase intention prediction due to constraints on data volume and hyperparameter selection.To address this issue,based on the deep forest algorithm and further integrating evolutionary ensemble learning methods,this paper proposes a novel Deep Adaptive Evolutionary Ensemble(DAEE)model.This model introduces model diversity into the cascade layer,allowing it to adaptively adjust its structure to accommodate complex and evolving purchasing behavior patterns.Moreover,this paper optimizes the methods of obtaining feature vectors,enhancement vectors,and prediction results within the deep forest algorithm to enhance the model’s predictive accuracy.Results demonstrate that the improved deep forest model not only possesses higher robustness but also shows an increase of 5.02%in AUC value compared to the baseline model.Furthermore,its training runtime speed is 6 times faster than that of deep models,and compared to other improved models,its accuracy has been enhanced by 0.9%.

Promoting sustainable consumption and circular economy:the intention of Vietnamese youth consumers to purchase products made from recycled plastics

Recycling is viewed as a key component in a circular economy and serves as an ideal solution for promoting sustainability.During the global plastic crisis,plastic recycling practices have been adopted worldwide,leading to the production of various products made from recycled plastics(PRP).Nevertheless,a gap persists between consumption and demand for such products,which is primarily attributed to a lack of comprehension from the consumer perspective.Given the pivotal role consumers play in the adoption of these products,this study explores consumers’intentions to purchase PRP.This is particularly significant in Vietnam,which is an emerging economy aspiring to achieve the objectives of a circular economy and sustainable development.Utilizing an integrated cognitive-emotional framework comprising the Valence Theory and the Norm Activation Model,data from 564 Vietnamese students were gathered and analyzed using structural equation modeling.The results show that awareness of consequences is a major driver of consumer purchase intentions,followed by perceived ease of application and monetary incentives.The results also indicate that health concerns have the strongest effect on purchase intention and in the negative side,meaning that the health-related risk is the primary concern for consumers during the decision-making process.This research holds substantial value for academics and managers,as it aids in the theoretical exploration and the formulation of strategies to improve consumer acceptance of PRP.

Empirical Analysis on Factors Affecting Mobile Internet Users’ Purchase Intention for 3G Handsets

The research on consumers' purchase intention for 3G handsets has important theoretical and practical value. This research puts forward four key factors which influence consumers' purchase intention based on the cue utilization theory, situational theory and social impact theory, then it establishes the study model for consumers' purchase intention of 3G handsets. Based on the result of the questionnaire survey and empirical analysis, the study shows that social influence is the most prominent factor in purchase intention. Moreover, as different from results of previous studies, the situational influence factors have no significant impact on purchase intention in the 3G handsets market. The results of the model provides a forceful evidence for operators' and handset manufacturers' decision-making of 3G handsets design and marketing strategies, and it will improve their social impact.

Theoretical Analysis of Consumers’Purchase Motivation in the Context of Environmental Protection

Through reviewing and summarizing the existing research on consumer motivation,and combining the characteristics of human behavior and the objective needs of environmental protection,this paper analyzes and defines consumers’purchase motivation.In the context of environmental protection,purchase motivation is divided into demand motivation,value recognition motivation,recognition motivation,and interest motivation.Their definitions are given in this paper,which provides a conceptual basis for further research on the influence of purchase motivation on consumer behavior in the context of environmental protection.

The Impact of E-Commerce Live Broadcasts on Consumers’Purchase Intention

E-commerce live broadcast has an important influence on consumers’purchase intention.The three dimensions of live broadcast content in the broadcast room are the number of comments,product quality,and live content as independent variables.A theoretical model is constructed with perceived value and risk as intermediaries and the consumers’purchase intention as the dependent variable,and corresponding hypotheses are put forward.We designed the scale,collected relevant data,and tested the model hypothesis using Statistical Package for Social Sciences(SPSS)and Analysis of Moment Structure(AMOS)software.The study found that the number of comments and product quality had a significant impact on perceived value,perceived risk,and consumers’purchase intention.From this conclusion,it is suggested that businesses should control the number of comments,strengthen the product quality of comments,and distinguish the repetition degree of the content of live broadcasts.

A Study on the Factors Influencing Consumer Purchase Decision Under the Live-Streaming Sales Model

In recent years,with the rapid development and popularization of Internet information technology,many new media platforms have risen rapidly,and major e-commerce companies have begun to explore the mode of livestreaming.Especially during the COVID-19 pandemic,due to the lockdown,live-streaming has become an important means of economic development in many places.Owing to its remarkable characteristics of timeliness,entertainment,and interactivity,it has become the latest and trendiest sales mode of e-commerce channels,reflecting huge economic potential and commercial value.This article analyzes two models and their characteristics of live-streaming sales from a practical perspective.Based on this,it outlines consumer purchasing decisions and the factors that affect consumer purchasing decisions under the live-streaming sales model.Finally,it discusses targeted suggestions for using the live-streaming sales model to expand the consumer market,hoping to promote the healthy and steady development of the live-streaming sales industry.

Optimization purchase price and the profit policy undervendor managed inventory

The optimization policy of the purchase price and the profit under vendor managed inventory(VMI) is studied. For a salable product, supply chain mode of VMI is established, which is based on deterministic demand, having initial stock and having stock-out cost. With the further analysis of the mode, VMI is found to increase profits of the buyer in the short-term motivation. But VMI will reduce profits of the supplier under the matching condition. And in the short-term motivation, VMI will increase the purchase price to compensate the transfer cost of the supplier. As a result, the foundation of theory is provided to implement VMI in the supply chain, and have some definituded project significance.

The Influence of Perceived Risk on Purchase Intention——A Case study of Taobao Online Shopping of Fresh Fruit

Based on perceived risk,the impacts of different kinds of risks on consumer's purchase intention are tested by using the investigation data of 2016,and perceived risks of consumers from different groups have different impacts on purchase intention. Via interviews and online questionnaires,425 copies of effective samples were obtained. The structural equation modeling is used for research. Results display that product risk significantly affects purchase intention,and perceived risk among different groups has significant difference. According to research conclusion,the authors think that consumer should actively collect all kinds of information and take effective risk avoidance measures; Taobao platform should continuously perfect purchase rule,punish the behavior of leaking buyers' information,and continuously update Alipay software to prevent hacker intrusion; business should guarantee product quality,open information and make scientific marketing strategy.

Demand prediction and purchase optimization decision model for alloys in steel making

In this study,related models of alloy purchasing decision system in the Baoshan base of Baosteel are discussed.First,the corresponding relationship between steel grades and alloy consumption is established through metallurgical-mechanism modeling and statistical analysis.Then,the alloy-demand prediction model based on alloy unit consumption and time series analysis is developed by combining sales plans and historical data.Finally,the alloy purchasing and inventory optimization model is developed to minimize the total cost of purchase and storage by combining inventory optimization theories.

Influence Mechanism of Clothing Anchor Features on Consumers'Purchase Intention

Relying on the field of e-commerce live broadcast,the features of clothing anchors are divided into four dimensions:charm features,recommendation features,display features and interaction features.The intermediate variable of social presence is introduced to construct a theoretical model of e-commerce live broadcast consumers'purchase intention.Based on the questionnaire survey data collection,using SPSS 23.0 software and Amos 23.0 software to analyze the data,it is concluded that the features of charm,recommendation,display and interaction of the clothing anchors have a significant positive impact on consumers'purchase intentions.Social presence plays a mediating role in the influence of the features of charm,recommendation,display and interaction on consumer'purchase intention.

The Impacts of Agricultural Machinery Purchase Subsidies on Mechanized Crop Residue Recycling

Crop residue recycling can improve the quality of the cropland,and it has multiple economic and ecological benefits.However,such practice is with low adoption due to different constraints.In this paper,we use the survey data from Baoding,Hebei province,and use the probit model to explore how the agricultural machinery purchase subsidies affect the mechanized crop residue recycling.The results showed that several factors that affect farmers in adopting the practice of mechanized crop residue crop recycling.Among these factors,the cost of adopting such practice is significant.The agricultural machinery purchase subsidies can effectively reduce the cost of such practice,as well as promote mechanized crop residue recycling.The paper also proposed several actions in the future.They include increasing the subsidies on agricultural machinery purchase and increasing farmers' awareness on crop residue recycling.

Consumers'Purchase Intention of Geographical Indication Agricultural Products under the Background of Live-streaming Sales:An Exploratory Research Based on Grounded Theory

Exploring the mechanism for the formation of consumer purchase intentions of geographical indication agricultural products in the context of live-streaming sales can provide an important reference for brand marketing of geographical indication agricultural products.In this study,in-depth interviews were conducted with consumers of geographical indication agricultural products.Based on grounded theory,open coding,axial coding and selective coding were performed for interview text.Finally,21 concepts,7 subcategories and 3 main categories were obtained,and a model of the formation mechanism of the purchase intention of geographical indication agricultural products under the background of live-streaming sales was constructed,that is,"consumer cognition-consumer attitude-consumer behavior".Among them,consumer cognition includes two dimensions:the type of geographical indication agricultural products and the live-streaming appeal strategy,i.e.,the personal cognition of consumer and the promotion of live-streaming host's strategy.Consumer attitude is value perception of consumers,mainly including two dimensions of functional value and emotional value.Consumer behavior is the consumer's willingness to buy.It has been concluded that the types of geographical indication agricultural products interact with the live-streaming appeal strategies.Through the intermediary of consumers'value perception,consumers'purchase intention is generated.Among them,resource-oriented geographical indication agricultural products adopt rational live-streaming appeal strategies,which can enhance the consumer's perception of functional value,thereby promoting their purchase intention;and cultural and creative geographical indication agricultural products brands adopt perceptual live-streaming appeal strategies,which can enhance the emotional value perception of consumers,thereby promoting their purchase intention.

Motives Underlying Organic Food Consumption in Turkey： Impact of Health, Environment, and Consumer Values on Purchase Intentions

Raising ecological awareness and health concerns create question marks about healthiness and sustainability of conventional foods in customers＇ minds. Due to augmented mass media coverage of environmental problems, health concerns related to consumption of genetically modified food and/or chemical contaminants in food, and consumers＇ increasing interest in healthy nutrition and environmental protection, there is a growing interest for organic foods in all over the world. Growing interest for organic foods, and increasing production and demand in organic food market has made organic food consumption a significant topic of research. Although organic food market and demand for organic foods have also been growing in Turkey, literature regarding organic food consumption is not very extensive. Therefore, this study aims to understand the underlying motives for organic food consumption in Turkey, and to explore the factors affecting Turkish consumers＇ attitudes towards organic foods and the behavioral intention of Turkish consumers to purchase organic food by the help of the theory of reasoned action （TRA）. The results of 622 successful surveys used for this empirical research indicate that Turkish consumers＇ attitudes towards organic foods are determined by perception of organic foods, consumer values, and price perception, while their purchase intention is determined by health consciousness, perception of organic foods, consumer values, price perception, and environmental concerns.

Antecedents of Microblogging Users’Purchase Intention Toward Celebrities’Merchandise:Perspectives of Virtual Community and Fan Economy

Over the last few decades,cross-fertilization between marketing and fandom studies in a mediated world has been rare,hindering the knowledge development for marketing practitioners in the Chinese fan economy context.The purpose of this study is to find and establish a conceptual framework that includes Online Interaction(OI),Parasocial Relationships(PSR)and virtual fan communities on Weibo,and how these contributory factors embedded in the interplay process of digital fandom practices in terms of enhancing fans’Purchase Intention(PI)and media consumption behaviours toward the celebrities’merchandise.Using an online survey instrument,this research collected 294 completed responses from fans who had online interactions with celebrities and engagement of virtual fan communities on Weibo.Key results and findings provided a clear framework of four antecedents based on the conceptual model and indicated that the high intensity of OI led to higher levels of the perception of PSR and the Sense of Virtual Community(SOVC).Increased PSR and the SOVC can be seen as significant positive predictors of the PI(a part of consumer identity construction as a fan)also.This study revealed the underlying mechanism of an emerging marketing genre,also provide useful implications of audiences’digital marketing practices for marketers,celebrities and policymakers.

Dynamic Promotional Resource Allocation for Segment Specific and Spectrum Effect of Promotion for a Product Line Incorporating Repeat Purchase Behavior

Promotion is an essential element in the marketing mix. It is used by businesses to inform, influence and persuade customers to adopt the products and services they offer. Without promotion, business would be stagnant and lack substantial growth because the brands would have low visibility in the market. Moreover, today’s vast and assorted markets comprise of customers with different needs and varied behavior. So it is rarely possible for companies to satisfy all customers by treating them alike. Thus there arises a need to divide the market into segments having customers with similar traits/characteristics. After identifying appropriate market segments, firms can design differentiated promotional campaigns for each segment. At the same time there can be a mass market promotional campaign that reaches different segments with a fixed spectrum. Also since promotional effort resources are limited, one must use them judiciously. In this paper, we formulate mathematical programming problem under repeat purchase scenario, which optimally allocates mass promotional effort resources and differentiated promotional effort resources across the segments dynamically in order to maximize the overall sales obtained from multiple products of a product line under budgetary and minimum sales aspiration level constraint on each product under consideration in each segment. The planning horizon is divided into multi periods, the adoption pattern of each product in each segment is observed in every subinterval and accordingly promotional effort allocations are determined for the next period till we reach the end of planning period. The optimization model has been further extended to incorporate minimum aspiration level constraints on total sales for each product under consideration from all the segments taken together. The non linear programming problem so formulated is solved using differential evolution approach. A numerical example has been discussed to illustrate applicability of the model.

The impact of consumer perceived value on repeat purchase intention based on online reviews: by the method of text mining

The progress of IT technology such as social network and mobile payment and the change of social economic environment promote the emergence of sharing economy.As a subversive business model,the sharing economy is growing at an alarming rate all over the world.However,the influencing factors of consumers'continuous participation in the sharing economy are not clear.The paper aims to clarify the relationship between consumer perceived value and repeat purchase intention in the sharing economy.Taking the sharing economy platform(Airbnb)as an example,it proposes a dimension framework of consumer perceived value in peer-to-peer(P2P)accommodation rental service,including functional value,hedonic value,epistemic value and social relationship value.This paper used big data technology to crawl online reviews of P2P accommodation platform.LDA(Latent Dirichlet Allocation)topic model and sentiment analytics method were applied to construct the measurement indicators of perceived value based on online reviews.And repeat purchase intention variables were extracted from online reviews.Then structural equation model was used to examine the effect of perceived value dimensions on it.The paper identified that perceived value has a positive impact on consumers'repurchase intention in P2P accommodation.Also,social relationship value was considered as the most important influencing factor.

A Grey Decision Model Used in Bidding for Equipment Purchase

Bidding has long been used as a method for allocating and procuring goods and services. An acurrate and comprehensive evaluation of bidders is the key to make the bidding a successful one for tenderee. However, evaluation of bidders is a tough work and the result of evaluation is always affected by the evaluator's understanding of the standards set for evaluation, and the evaluator's expertise, experience and preferrence. We make an effort to find a method for selecting bidders as accurately as possible. A grey decision model is presented, and an example is illustrated to make the practioners know how to use the model.

The Business of Managing Risk and Network Security:An Exploration of Knowledge Transfer Issues within the Context of Data Security and Countermeasure Trade Offs

The contemporary environment within which command,control,communications,computers and intelligence (C4I platforms exist, have a number of characteristics. These characteristics may be most obviously identified as interconnectivity, international networking, speed of data transfer, the compact nature of electronic information and rapidly changing technology. Information security professionals employ a variety of approaches in order to counter risks within this complex and fluid environment. The gamut of potential security activities ranges form access control through a variety of auditing techniques to secure data communications. This field is broad and well documented. Indeed, the discipline of network risk management and data security is both well developed and sophisticated.This paper addresses twin themes:i.The fundamental issue of the method by which specific approaches are employed. This is a precursor to the adoption of an eventual strategy.ii.The crucial issues revolving around the

Prediction of users online purchase behavior based on selective ensemble learning

A probabilistic multi-dimensional selective ensemble learning method and its application in the prediction of users' online purchase behavior are studied in this work.Firstly, the classifier is integrated based on the dimension of predicted probability, and the pruning algorithm based on greedy forward search is obtained by combining the two indicators of accuracy and complementarity.Then the pruning algorithm is integrated into the Stacking ensemble method to establish a user online shopping behavior prediction model based on the probabilistic multi-dimensional selective ensemble method.Finally, the research method is compared with the prediction results of individual learners in ensemble learning and the Stacking ensemble method without pruning.The experimental results show that the proposed method can reduce the scale of integration, improve the prediction accuracy of the model, and predict the user's online purchase behavior.

A Protocol for Fair Electronic Purchase Based on Concurrent Signatures

E-commerce protocols for the electronic purchase of goods are difficult to design and implement due to their complexity and high security demands. Fairness of such protocols in literature highly depends on an additional TTP（trusted third party）. However, it is difficult to find such a TTP in some situations. In addition, fairness for customers has been neither fully considered nor well satisfied in existing electronic purchasing protocols. In this paper, a new protocol FEP （fair electronic purchase） without a special TTP but an online bank is presented based on a concurrent digital signature scheme. The FEP protocol guarantees fair electronic purchase of goods via electronic payment between consumers, merchants and their online banks. The protocol is practical and the analysis based on the game logics shows that it achieves the properties of viability, fairness, and timeliness.